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V. K. Goar, N. S. Yadav, M. Kuri, Sentimental and time series study of coronavirus immunization tweets using VADER, Journal of Collective Sciences and Sustainability, 2025, 1(1), 25404, doi: https://doi.org/10.64189/css.25404.

Abstract

A suitable platform for sentiment analysis of people is one of the hidden advantages of social channels. This has led to drawing the focus of various research communities and hence sentimental study has gained much awareness in recent years. Among the available options, Twitter happens to be the most accepted of all functional platforms. Identifying the well-defined methodology or technique for sentimental study related to data available on Twitter concerns the selection of an eligible set of data and such study of results is the prime focus of our research. In this research, there is an analysis of public sentiments expressed in the Twitter database regarding the COVID-19 vaccine. With a flood of information-carrying myth and reality about COVID-19 vaccine vegetation of uncertainties, the component of excitement and fear started growing across the globe. The polarity of sentiments that could be of any type i.e. neutral, positive, negative when identified on a time scale generates trend analysis for a suitable approach. After capturing public thoughts, opinions and feelings systematic literature review is performed and an investigational prototype is generated in order to scatter the sentiments on the inspected data & recognize the everyday sentiment over the span of the timeline. Documentation of fluctuations in daily sentiments is shown through time series analysis. This research reflects the set of data related to tweets captured from September 21 - March 22. As per our findings, the Valence Aware Dictionary and sentiment Reasoner (VADER) sentiment analyzer is the best and most effective model to get optimal results from the collected sentiments, and the polarity score is recorded over some time. This research enhances the interpretation of the public’s point of view on coronavirus immunization and helps them focus on removing covid-19 from the rest of the world.

Graphical Abstract

Novelty statement

The VADER sentiment analyzer is the best and most effective model to get optimal results from the collected sentiments, and the polarity score is recorded over some time.